renaissance-movie-lens_0
[2024-11-08T05:54:06.606Z] Running test renaissance-movie-lens_0 ...
[2024-11-08T05:54:06.606Z] ===============================================
[2024-11-08T05:54:06.606Z] renaissance-movie-lens_0 Start Time: Fri Nov 8 05:54:05 2024 Epoch Time (ms): 1731045245709
[2024-11-08T05:54:06.606Z] variation: NoOptions
[2024-11-08T05:54:06.606Z] JVM_OPTIONS:
[2024-11-08T05:54:06.606Z] { \
[2024-11-08T05:54:06.606Z] echo ""; echo "TEST SETUP:"; \
[2024-11-08T05:54:06.606Z] echo "Nothing to be done for setup."; \
[2024-11-08T05:54:06.606Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17310444131442/renaissance-movie-lens_0"; \
[2024-11-08T05:54:06.606Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17310444131442/renaissance-movie-lens_0"; \
[2024-11-08T05:54:06.606Z] echo ""; echo "TESTING:"; \
[2024-11-08T05:54:06.607Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17310444131442/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-08T05:54:06.607Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17310444131442/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-08T05:54:06.607Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-08T05:54:06.607Z] echo "Nothing to be done for teardown."; \
[2024-11-08T05:54:06.607Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17310444131442/TestTargetResult";
[2024-11-08T05:54:06.607Z]
[2024-11-08T05:54:06.607Z] TEST SETUP:
[2024-11-08T05:54:06.607Z] Nothing to be done for setup.
[2024-11-08T05:54:06.607Z]
[2024-11-08T05:54:06.607Z] TESTING:
[2024-11-08T05:54:08.657Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-08T05:54:10.212Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-11-08T05:54:13.588Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-08T05:54:14.352Z] Training: 60056, validation: 20285, test: 19854
[2024-11-08T05:54:14.352Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-08T05:54:14.352Z] GC before operation: completed in 180.629 ms, heap usage 141.688 MB -> 27.174 MB.
[2024-11-08T05:54:19.944Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T05:54:23.322Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T05:54:26.734Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T05:54:30.159Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T05:54:31.746Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T05:54:34.218Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T05:54:35.834Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T05:54:38.299Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T05:54:38.299Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T05:54:38.299Z] The best model improves the baseline by 14.52%.
[2024-11-08T05:54:38.299Z] Movies recommended for you:
[2024-11-08T05:54:38.299Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T05:54:38.299Z] There is no way to check that no silent failure occurred.
[2024-11-08T05:54:38.299Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (24261.892 ms) ======
[2024-11-08T05:54:38.299Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-08T05:54:38.299Z] GC before operation: completed in 322.969 ms, heap usage 126.316 MB -> 40.860 MB.
[2024-11-08T05:54:41.716Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T05:54:45.136Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T05:54:48.554Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T05:54:51.979Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T05:54:53.578Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T05:54:56.040Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T05:54:57.637Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T05:54:59.767Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T05:54:59.767Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T05:55:00.532Z] The best model improves the baseline by 14.52%.
[2024-11-08T05:55:00.532Z] Movies recommended for you:
[2024-11-08T05:55:00.532Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T05:55:00.532Z] There is no way to check that no silent failure occurred.
[2024-11-08T05:55:00.532Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21599.596 ms) ======
[2024-11-08T05:55:00.532Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-08T05:55:00.532Z] GC before operation: completed in 207.107 ms, heap usage 183.833 MB -> 42.220 MB.
[2024-11-08T05:55:02.997Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T05:55:06.406Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T05:55:08.873Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T05:55:12.300Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T05:55:13.882Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T05:55:15.707Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T05:55:16.476Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T05:55:18.064Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T05:55:18.830Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T05:55:18.830Z] The best model improves the baseline by 14.52%.
[2024-11-08T05:55:18.830Z] Movies recommended for you:
[2024-11-08T05:55:18.830Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T05:55:18.830Z] There is no way to check that no silent failure occurred.
[2024-11-08T05:55:18.830Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (18178.790 ms) ======
[2024-11-08T05:55:18.830Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-08T05:55:18.830Z] GC before operation: completed in 209.495 ms, heap usage 433.540 MB -> 46.378 MB.
[2024-11-08T05:55:21.293Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T05:55:24.712Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T05:55:27.186Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T05:55:29.659Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T05:55:31.248Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T05:55:32.878Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T05:55:34.465Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T05:55:36.053Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T05:55:36.819Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T05:55:36.820Z] The best model improves the baseline by 14.52%.
[2024-11-08T05:55:36.820Z] Movies recommended for you:
[2024-11-08T05:55:36.820Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T05:55:36.820Z] There is no way to check that no silent failure occurred.
[2024-11-08T05:55:36.820Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17745.162 ms) ======
[2024-11-08T05:55:36.820Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-08T05:55:36.820Z] GC before operation: completed in 174.748 ms, heap usage 398.164 MB -> 46.775 MB.
[2024-11-08T05:55:39.287Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T05:55:41.855Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T05:55:45.276Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T05:55:49.238Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T05:55:51.745Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T05:55:55.179Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T05:55:58.648Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T05:56:01.126Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T05:56:01.906Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T05:56:01.906Z] The best model improves the baseline by 14.52%.
[2024-11-08T05:56:01.906Z] Movies recommended for you:
[2024-11-08T05:56:01.906Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T05:56:01.906Z] There is no way to check that no silent failure occurred.
[2024-11-08T05:56:01.906Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (24991.594 ms) ======
[2024-11-08T05:56:01.906Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-08T05:56:01.906Z] GC before operation: completed in 239.003 ms, heap usage 400.215 MB -> 46.963 MB.
[2024-11-08T05:56:07.543Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T05:56:13.171Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T05:56:18.808Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T05:56:23.303Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T05:56:27.806Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T05:56:31.253Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T05:56:33.746Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T05:56:37.194Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T05:56:37.194Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T05:56:37.194Z] The best model improves the baseline by 14.52%.
[2024-11-08T05:56:37.194Z] Movies recommended for you:
[2024-11-08T05:56:37.194Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T05:56:37.194Z] There is no way to check that no silent failure occurred.
[2024-11-08T05:56:37.194Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (35297.741 ms) ======
[2024-11-08T05:56:37.194Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-08T05:56:37.960Z] GC before operation: completed in 328.994 ms, heap usage 365.805 MB -> 43.595 MB.
[2024-11-08T05:56:44.425Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T05:56:50.048Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T05:56:55.715Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T05:57:01.363Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T05:57:03.855Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T05:57:06.357Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T05:57:09.936Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T05:57:12.440Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T05:57:12.440Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T05:57:12.440Z] The best model improves the baseline by 14.52%.
[2024-11-08T05:57:13.294Z] Movies recommended for you:
[2024-11-08T05:57:13.294Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T05:57:13.294Z] There is no way to check that no silent failure occurred.
[2024-11-08T05:57:13.294Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (35236.770 ms) ======
[2024-11-08T05:57:13.294Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-08T05:57:13.294Z] GC before operation: completed in 265.939 ms, heap usage 413.108 MB -> 47.260 MB.
[2024-11-08T05:57:17.814Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T05:57:22.297Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T05:57:27.921Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T05:57:32.914Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T05:57:35.398Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T05:57:37.911Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T05:57:40.400Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T05:57:43.857Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T05:57:43.857Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T05:57:43.857Z] The best model improves the baseline by 14.52%.
[2024-11-08T05:57:43.857Z] Movies recommended for you:
[2024-11-08T05:57:43.857Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T05:57:43.857Z] There is no way to check that no silent failure occurred.
[2024-11-08T05:57:43.857Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (30764.391 ms) ======
[2024-11-08T05:57:43.857Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-08T05:57:43.857Z] GC before operation: completed in 294.981 ms, heap usage 387.933 MB -> 47.370 MB.
[2024-11-08T05:57:49.501Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T05:57:53.973Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T05:57:58.470Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T05:58:04.083Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T05:58:06.585Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T05:58:09.058Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T05:58:11.548Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T05:58:15.098Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T05:58:15.098Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T05:58:15.098Z] The best model improves the baseline by 14.52%.
[2024-11-08T05:58:15.098Z] Movies recommended for you:
[2024-11-08T05:58:15.098Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T05:58:15.098Z] There is no way to check that no silent failure occurred.
[2024-11-08T05:58:15.098Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (30846.102 ms) ======
[2024-11-08T05:58:15.098Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-08T05:58:15.098Z] GC before operation: completed in 276.091 ms, heap usage 366.829 MB -> 43.858 MB.
[2024-11-08T05:58:20.739Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T05:58:25.225Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T05:58:29.926Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T05:58:34.409Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T05:58:36.887Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T05:58:39.360Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T05:58:42.821Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T05:58:45.327Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T05:58:45.327Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T05:58:45.327Z] The best model improves the baseline by 14.52%.
[2024-11-08T05:58:45.327Z] Movies recommended for you:
[2024-11-08T05:58:45.327Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T05:58:45.327Z] There is no way to check that no silent failure occurred.
[2024-11-08T05:58:45.327Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (30269.974 ms) ======
[2024-11-08T05:58:45.327Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-08T05:58:46.101Z] GC before operation: completed in 358.542 ms, heap usage 384.119 MB -> 47.305 MB.
[2024-11-08T05:58:50.585Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T05:58:55.082Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T05:58:59.611Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T05:59:05.272Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T05:59:06.873Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T05:59:10.307Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T05:59:12.800Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T05:59:15.348Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T05:59:16.122Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T05:59:16.122Z] The best model improves the baseline by 14.52%.
[2024-11-08T05:59:16.122Z] Movies recommended for you:
[2024-11-08T05:59:16.122Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T05:59:16.122Z] There is no way to check that no silent failure occurred.
[2024-11-08T05:59:16.122Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (30086.905 ms) ======
[2024-11-08T05:59:16.122Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-08T05:59:16.122Z] GC before operation: completed in 281.708 ms, heap usage 353.623 MB -> 43.434 MB.
[2024-11-08T05:59:21.111Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T05:59:25.615Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T05:59:31.233Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T05:59:35.722Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T05:59:38.206Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T05:59:40.699Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T05:59:43.205Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T05:59:46.657Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T05:59:46.657Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T05:59:46.657Z] The best model improves the baseline by 14.52%.
[2024-11-08T05:59:46.657Z] Movies recommended for you:
[2024-11-08T05:59:46.657Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T05:59:46.657Z] There is no way to check that no silent failure occurred.
[2024-11-08T05:59:46.657Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (30487.930 ms) ======
[2024-11-08T05:59:46.657Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-08T05:59:46.657Z] GC before operation: completed in 225.819 ms, heap usage 369.940 MB -> 43.899 MB.
[2024-11-08T05:59:52.285Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T05:59:56.775Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T06:00:01.254Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T06:00:05.721Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T06:00:09.134Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T06:00:11.592Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T06:00:14.073Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T06:00:17.158Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T06:00:17.158Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T06:00:17.931Z] The best model improves the baseline by 14.52%.
[2024-11-08T06:00:17.931Z] Movies recommended for you:
[2024-11-08T06:00:17.931Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T06:00:17.931Z] There is no way to check that no silent failure occurred.
[2024-11-08T06:00:17.931Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (30665.888 ms) ======
[2024-11-08T06:00:17.931Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-08T06:00:17.931Z] GC before operation: completed in 244.479 ms, heap usage 396.475 MB -> 47.408 MB.
[2024-11-08T06:00:22.462Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T06:00:26.907Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T06:00:32.523Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T06:00:36.961Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T06:00:39.430Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T06:00:42.853Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T06:00:45.318Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T06:00:47.778Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T06:00:48.551Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T06:00:48.551Z] The best model improves the baseline by 14.52%.
[2024-11-08T06:00:48.551Z] Movies recommended for you:
[2024-11-08T06:00:48.551Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T06:00:48.551Z] There is no way to check that no silent failure occurred.
[2024-11-08T06:00:48.551Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (30568.222 ms) ======
[2024-11-08T06:00:48.551Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-08T06:00:48.551Z] GC before operation: completed in 230.142 ms, heap usage 391.583 MB -> 47.091 MB.
[2024-11-08T06:00:53.008Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T06:00:58.600Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T06:01:03.056Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T06:01:08.631Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T06:01:11.416Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T06:01:14.838Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T06:01:17.392Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T06:01:20.841Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T06:01:21.604Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T06:01:21.604Z] The best model improves the baseline by 14.52%.
[2024-11-08T06:01:21.604Z] Movies recommended for you:
[2024-11-08T06:01:21.604Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T06:01:21.604Z] There is no way to check that no silent failure occurred.
[2024-11-08T06:01:21.604Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (32733.481 ms) ======
[2024-11-08T06:01:21.604Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-08T06:01:21.605Z] GC before operation: completed in 240.010 ms, heap usage 365.624 MB -> 44.031 MB.
[2024-11-08T06:01:27.185Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T06:01:32.774Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T06:01:39.606Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T06:01:44.068Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T06:01:47.503Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T06:01:49.984Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T06:01:53.407Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T06:01:55.868Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T06:01:56.643Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T06:01:56.643Z] The best model improves the baseline by 14.52%.
[2024-11-08T06:01:56.643Z] Movies recommended for you:
[2024-11-08T06:01:56.643Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T06:01:56.643Z] There is no way to check that no silent failure occurred.
[2024-11-08T06:01:56.643Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (34793.090 ms) ======
[2024-11-08T06:01:56.643Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-08T06:01:56.643Z] GC before operation: completed in 262.963 ms, heap usage 366.956 MB -> 44.110 MB.
[2024-11-08T06:02:02.238Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T06:02:06.153Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T06:02:11.759Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T06:02:16.244Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T06:02:19.678Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T06:02:22.161Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T06:02:24.629Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T06:02:27.104Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T06:02:27.869Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T06:02:27.869Z] The best model improves the baseline by 14.52%.
[2024-11-08T06:02:27.869Z] Movies recommended for you:
[2024-11-08T06:02:27.869Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T06:02:27.869Z] There is no way to check that no silent failure occurred.
[2024-11-08T06:02:27.869Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (31137.696 ms) ======
[2024-11-08T06:02:27.869Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-08T06:02:27.869Z] GC before operation: completed in 260.440 ms, heap usage 371.289 MB -> 43.955 MB.
[2024-11-08T06:02:33.473Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T06:02:37.960Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T06:02:42.434Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T06:02:46.901Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T06:02:50.333Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T06:02:52.793Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T06:02:55.265Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T06:02:58.239Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T06:02:58.239Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T06:02:58.239Z] The best model improves the baseline by 14.52%.
[2024-11-08T06:02:58.239Z] Movies recommended for you:
[2024-11-08T06:02:58.239Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T06:02:58.239Z] There is no way to check that no silent failure occurred.
[2024-11-08T06:02:58.239Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (30219.350 ms) ======
[2024-11-08T06:02:58.239Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-08T06:02:58.239Z] GC before operation: completed in 211.523 ms, heap usage 377.856 MB -> 47.267 MB.
[2024-11-08T06:03:03.841Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T06:03:08.295Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T06:03:12.774Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T06:03:17.322Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T06:03:19.783Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T06:03:22.344Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T06:03:25.792Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T06:03:28.728Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T06:03:28.728Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T06:03:28.728Z] The best model improves the baseline by 14.52%.
[2024-11-08T06:03:28.728Z] Movies recommended for you:
[2024-11-08T06:03:28.728Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T06:03:28.728Z] There is no way to check that no silent failure occurred.
[2024-11-08T06:03:28.728Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (29956.013 ms) ======
[2024-11-08T06:03:28.728Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-08T06:03:28.728Z] GC before operation: completed in 274.747 ms, heap usage 360.707 MB -> 44.203 MB.
[2024-11-08T06:03:33.283Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T06:03:38.898Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T06:03:43.368Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T06:03:47.813Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T06:03:50.283Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T06:03:52.740Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T06:03:56.171Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T06:03:58.636Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T06:03:59.396Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-08T06:03:59.396Z] The best model improves the baseline by 14.52%.
[2024-11-08T06:03:59.396Z] Movies recommended for you:
[2024-11-08T06:03:59.396Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T06:03:59.396Z] There is no way to check that no silent failure occurred.
[2024-11-08T06:03:59.396Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (30412.391 ms) ======
[2024-11-08T06:04:00.161Z] -----------------------------------
[2024-11-08T06:04:00.161Z] renaissance-movie-lens_0_PASSED
[2024-11-08T06:04:00.161Z] -----------------------------------
[2024-11-08T06:04:00.161Z]
[2024-11-08T06:04:00.161Z] TEST TEARDOWN:
[2024-11-08T06:04:00.161Z] Nothing to be done for teardown.
[2024-11-08T06:04:00.161Z] renaissance-movie-lens_0 Finish Time: Fri Nov 8 06:03:59 2024 Epoch Time (ms): 1731045839674